• Academy Events

  • 9th Annual Machine Learning Symposium

    Friday, March 13, 2015 | 9:00 AM - 5:00 PM
    The New York Academy of Sciences

    Presented by the Machine Learning Discussion Group at the New York Academy of Sciences

    In our current digital age, a wealth of data is available at our fingertips. Often, the value of this 'Big Data' is not in the data itself, but in the ability to learn from it in order to make predictions. Machine Learning, a branch of artificial intelligence, involves the development of mathematical algorithms that discover knowledge from specific data sets, and then "learn" from the data in an iterative fashion that allows predictions to be made. Today, Machine Learning has a wide range of applications, including natural language processing, search engine functionality, medical diagnosis, credit card fraud detection, and stock market analysis.

    This symposium — part of an ongoing series presented by the Machine Learning Discussion Group at the New York Academy of Sciences — will feature Keynote Presentations from leading scientists in both applied and theoretical Machine Learning. Keynote Speakers include Pedro Domingos, Yoshua Bengio, and Elad Hazan.

    2015 Spotlight Talk Awards

    The New York Academy of Sciences congratulates the winners of the 2015 Spotlight Talk Awards, which recognized a series of the best oral research presentations delivered by early career investigators during the Symposium.

    Regret Minimization in Posted Price Auctions against Strategic Buyers
    Andres Muñoz Medina
    Courant Institute

    Large-Scale Clustering of Sentences and Patients based on Electronic Health Records
    Stefan Stark
    Memorial Sloan-Kettering Cancer Center

    Learning With Deep Cascades
    Giulia DeSalvo
    Courant Institute

    Achieving All with No Parameters: Adaptive NormalHedge
    Haipeng Luo
    Princeton University

    Approximate Kernel Methods for Speech Recognition and Computer Vision
    Avner May
    Columbia University

    Anchored Factor Analysis
    Yonatan Halpern
    New York University

    On-line Learning Approach to Ensemble Methods for Structured Prediction
    Vitaly Kuznetsov
    Courant Institute

    Probabilistic Bayesian Analysis of Genetic Associations with Clinical Features in Cancer
    Melanie Pradier
    Memorial Sloan-Kettering Cancer Center

    Theoretical Foundations for Learning Kernels in Supervised Kernel PCA
    Dmitry Storcheus
    Courant Institute (Currently Google)

    Finding a Sparse Vector in a Subspace: Linear Sparsity Using Alternating Directions
    Qing Qu
    Columbia University

    Google is the proud sponsor of the Spotlight Talk awards.


    Naoki Abe, IBM Research
    Corinna Cortes, Google
    Patrick Haffner, Interactions Corporation
    Tony Jebara, Columbia University
    John Langford, Microsoft Research
    Mehryar Mohri, Courant Institute of Mathematical Sciences, New York University
    Gunnar Rätsch, Memorial Sloan Kettering Cancer Center
    Greg Recine, The New York Academy of Sciences
    Robert Schapire, Microsoft Research and Princeton University
    Di Xu, American Express

    Mission Partner support for the Frontiers of Science program provided by   Pfizer